Please use this identifier to cite or link to this item: https://doi.org/10.1080/09511920601160148
DC FieldValue
dc.titleApplication of statistical process control in injection mould manufacturing
dc.contributor.authorCao, J.
dc.contributor.authorWong, Y.S.
dc.contributor.authorLee, K.S.
dc.date.accessioned2014-06-17T06:13:00Z
dc.date.available2014-06-17T06:13:00Z
dc.date.issued2007-07
dc.identifier.citationCao, J., Wong, Y.S., Lee, K.S. (2007-07). Application of statistical process control in injection mould manufacturing. International Journal of Computer Integrated Manufacturing 20 (5) : 436-451. ScholarBank@NUS Repository. https://doi.org/10.1080/09511920601160148
dc.identifier.issn0951192X
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/59569
dc.description.abstractShort-run statistical process control (SPC) usually transfers the data of different types of parts through data coding and part-family formation. As plastic injection moulds are mostly made in one-off or very small batches and one mould part can be very different from another, constant machine set-up changes are needed. In this situation, part-family formation becomes very difficult. The part family either becomes too large, introducing variations that are unnecessary or more complex to handle, or there are too many part families to handle. An approach is proposed in the present study with the aim to overcome the aforementioned problems. This approach defines the SPC processes and part families based on data from manufacturing processes in the mould manufacturing workshop. For each mould part to be produced, its manufacturing processes are classified into particular SPC processes, and the part is classified into a specific part family according to prescribed memberships. Through this procedure, unwanted variations are effectively isolated to facilitate and simplify subsequent data processing and interpretation. Domain-specific methods and rules of SPC planning for mould manufacturing are also presented to simplify the application of SPC in this area.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/09511920601160148
dc.sourceScopus
dc.subjectInjection mould
dc.subjectStatistical process control
dc.typeArticle
dc.contributor.departmentMECHANICAL ENGINEERING
dc.description.doi10.1080/09511920601160148
dc.description.sourcetitleInternational Journal of Computer Integrated Manufacturing
dc.description.volume20
dc.description.issue5
dc.description.page436-451
dc.description.codenICIME
dc.identifier.isiut000248333700004
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

4
checked on Nov 24, 2020

WEB OF SCIENCETM
Citations

3
checked on Nov 24, 2020

Page view(s)

108
checked on Nov 23, 2020

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.